AI / ML Engineer

Key Responsibilities :

• Lead the development and implementation of AI / ML models, specializing in deep learning techniques including supervised, unsupervised, self-supervised, and reinforcement learning.
• Architect and deploy solutions using Large Language Models (LLMs) including transformers, self-attention mechanisms, mixture of experts, and embeddings.
• Design and implement Retrieval Augmented Generation (RAG) systems integrating vector databases, graph databases, and cutting-edge prompt engineering techniques.
• Develop and optimize AI agents, including orchestration and performance tuning for complex workflows.
• Perform model fine-tuning, data pre-processing, and feature engineering to improve AI system accuracy and efficiency.
• Utilize ML frameworks such as PyTorch, TensorFlow, or equivalent for model development and experimentation.
• Work with AI / ML tooling such as LangChain, LangGraph (preferred), CrewAI, LlamaIndex, and LLMOps platforms like LangFuse (preferred) or LangSmith.
• Deploy AI / ML models and applications on AWS, leveraging services such as ECS, Lambda, S3, and AI / ML platforms like SageMaker and Bedrock.
• Employ containerization and orchestration technologies including Docker and Kubernetes for scalable and reliable AI deployments.
• Collaborate closely with cross-functional teams to deliver end-to-end AI solutions focused on reliability, scalability, and usability in production environments.
• Apply strong problem-solving skills to troubleshoot and resolve challenges throughout the AI model lifecycle.

Required Qualifications and Skills :

Preferred Qualifications :

(ref : hirist.tech)